INGREDIQ

Dog Food Advisor gets millions of monthly visits from pet owners manually researching ingredients — but it only covers specific named brands. No AI tool exists to let you paste any ingredient list and get an instant grade plus a plain-English breakdown of what each ingredient actually means for your pet.

IngredIQ fills that gap. Scan a barcode in the store, paste a Chewy URL at home, or photo-capture a label — get a letter grade (A–F), a flagged-ingredient list, a plain-English breakdown, and personalized notes based on your pet's breed, age, and known sensitivities.

Web for discovery (no download friction). App for in-store scan flow. Same output, different input method per context.

Web optimizes for discovery and URL sharing. App optimizes for the in-store aisle. Both hit the same AI analysis engine.

• Overall letter grade (A–F) with a one-line verdict
• Ingredient-by-ingredient breakdown in plain English
• Flagged ingredients: known harmful, controversial, filler, artificial
• Personalized notes based on pet profile (breed, age, weight, known allergies)
• FDA recall check — is this product or brand currently recalled?
• Alternative recommendations at same price tier with better grade

Two indie apps prove demand. Neither is polished. Neither covers web. Neither has recall alerts or real personalization. This isn't a blue ocean — it's a shallow pond with two weak fish. Win on execution.

• No ads — obvious conflict of interest when the product is dog food recommendations
• Flat subscription: ~$5–7/month or $49/year
• Free tier: limited scans/month (3–5) to prove value before paywall
• Avoid per-scan friction — removes spontaneous in-store use case

$7/month is impulse-buy territory for a pet owner already spending $50–200/month on food.

• r/dogs (3.8M) + r/cats (3M) — "I built a tool to decode your dog's food label" posts historically perform well
• Dog Food Advisor forums — already a captive audience of ingredient-obsessed pet owners
• SEO: "is [brand X] good for dogs?" queries get millions of monthly searches with no AI-native results
• TikTok: scan-and-grade videos are inherently visual, shareable format

• Pet profiles — personalized grades that follow your specific dog's needs
• FDA recall alerts — subscribe to get notified when any scanned product gets recalled
• Scan history — your full library of rated foods
• Food comparison — side-by-side grade two products

• Ingredient database: build curated from scratch, or bootstrap off AAFCO ingredient definitions + FDA data?
• Grading rubric: who defines A vs. B vs. F? Veterinary nutritionist consult needed?
• URL scraping: Chewy / Amazon ingredient lists are DOM-scraped — reliability varies by brand page format
• Cat food: same engine, separate positioning, or fold into v1?
• Recall data freshness: how often does FDA update the public recall feed?
• App store vs. web-first: does the scan use case require native app, or can PWA camera access suffice for MVP?